Consulting Engineer - ElasticSearch

Elastic, the Search AI Company, enables everyone to find the answers they need in real time using all their data at scale. As a Consulting Engineer – Search, you will help customers realize the value of Elastic’s solutions by designing and delivering scalable architectures that improve application performance and user experience.

Responsibilities:

• Translate business and technical requirements into scalable, outcome-driven solutions built on the Elastic Stack
• Lead end-to-end delivery of customer engagements — from discovery and design through implementation, enablement, and optimization
• Partner with customers to architect, deploy, and operationalize Elastic solutions that drive measurable value and adoption
• Provide technical oversight, guidance, and enablement to customers and teammates throughout project lifecycles
• Collaborate cross-functionally with Sales, Product, Engineering, and Support to ensure successful outcomes and continuous improvement
• Capture and share best practices, lessons learned, and solution patterns across the Elastic Services community
• Contribute to internal enablement, mentoring, and a culture of continuous learning and collaboration
• Apply your expertise to optimize queries, tune clusters, and handle high query/indexing throughput at enterprise scale
• Collaborate with product and engineering teams to identify product improvements, extensions, and defects based on field feedback
• Operationalize vector search (e.g., kNN, ANN, hybrid embeddings) with Elastic’s vector capabilities and ML models or similar
• Profile and tune queries for high-QPS environments with sub-second latency targets

Requirements:

• 5+ years as a consultant, engineer, or architect with deep expertise in Enterprise Search technologies and concepts, including generative AI
• Hands-on experience deploying Elastic Search solutions or similar platforms (Solr, Algolia, AWS OpenSearch, Palantir, Unbxd, e-commerce site search engines)
• Strong experience in custom search solution design, query development, relevancy tuning, and NLP use cases
• Expertise in distributed systems and large-scale application infrastructure
• Proficiency in at least one programming language; knowledge of open-source machine learning/AI frameworks preferred
• Knowledge or certification in Kubernetes, Linux, Java, databases, Docker, AWS/Azure/GCP, Kafka, Redis, VMs, Lucene
• Familiarity with DevOps practices: Docker, Kubernetes, Terraform, CI/CD
• Ability to manage delivery from proof-of-concept through production rollout, while mentoring client teams for long-term success
• Familiarity with modern NLP and AI ecosystems (transformers, Hugging Face, vector DBs like Pinecone or Weaviate) as applied to search
• Strong communication and presentation skills, with experience working directly with customers to gather requirements and deliver solutions
• Bachelor's, Master's, or PhD in Computer Science, Engineering, or related field, or equivalent experience
• Comfortable working in highly distributed teams, both remote and on-site when needed
• May require significant travel to customer sites to support engagements and solution implementations; candidates should be comfortable with varying levels of travel based on business needs
• Elastic Certified Engineer certification
• Experience at a Big 4 consulting firm
• Hands-on experience with Ansible, Terraform, JavaScript, ECK/Kubernetes
• Familiarity with machine learning and AI applied to search solutions
• Experience contributing to open-source projects or documentation
• Public speaking experience at conferences, meetups, or enterprise workshops